AVS 53rd International Symposium
    Applied Surface Science Thursday Sessions
       Session AS-ThA

Invited Paper AS-ThA3
Multi-technique, Multivariate Analysis Methods for Enhanced Sample Characterization

Thursday, November 16, 2006, 2:40 pm, Room 2005

Session: Combined Methods or Multiple Methods
Presenter: J.E. Fulghum, University of New Mexico
Authors: J.E. Fulghum, University of New Mexico
K. Artyushkova, University of New Mexico
S. Pylypenko, University of New Mexico
J.L. Fenton, University of New Mexico
K.M. Archuleta, University of New Mexico
L. Williams, University of New Mexcio
Correspondent: Click to Email
Characterization of heterogeneous samples frequently requires multi-technique correlations. The ability to acquire images from the same area on samples using multiple techniques provides opportunities for enhanced sample characterization, including using data from one technique to facilitate or confirm interpretation of data from a second technique. A variety of techniques, including AFM, FTIR, XPS and confocal microscopy (CM) have comparable fields-of-view, although spatial resolution and information content differ dramatically. This talk will incorporate a variety of examples of multi-technique correlations including visualization of 3-D polymer chemistry through correlation of XPS, CM and AFM data; fusion of high spatial resolution AFM images with high energy resolution XPS images for enhanced spatial distribution information; quantification of CM image data sets through fusion with XPS quantitative images, and correlation of AFM images with contact angle data. Correlating the data from multiple techniques, as in the examples listed above, requires matching and marking of the sample analysis areas, image registration, multivariate image analysis, image quantification and image fusion. We are currently developing a Matlab-based Graphical User Interface (GUI), that includes all of these steps. The goals of the GUI include managing images from multiple modalities, performing multiple imaging processing steps such as classification and PCA, segmentation, image registration, image fusion, volume reconstruction; providing tools that support flexibility by incorporating new and existing image analysis routines; and providing a simple, yet powerful user interface. The current status and availability of the GUI will be described.